Non-Graphical Solutions for Cattell's Scree Test

被引：200

作者：

Raiche, Gilles ^{[1
]}

Walls, Theodore A. ^{[2
]}

Magis, David ^{[3
,4
]}

Riopel, Martin ^{[1
]}

Blais, Jean-Guy ^{[5
]}

机构：

[1] Univ Quebec Montreal, Montreal, PQ H3C 3P8, Canada

[2] Univ Rhode Isl, Kingston, RI 02881 USA

[3] Univ Liege, B-4000 Liege, Belgium

[4] Katholieke Univ Leuven, Louvain, Belgium

[5] Univ Montreal, Montreal, PQ H3C 3J7, Canada

来源：

METHODOLOGY-EUROPEAN JOURNAL OF RESEARCH METHODS FOR THE BEHAVIORAL AND SOCIAL SCIENCES | 2013年 / 9卷 / 01期

关键词：

principal components analysis; number of components; dimensionality; eigenvalues; Cattell's scree plot; PARALLEL ANALYSIS; LATENT ROOTS; NUMBER; COMPONENTS; COVARIANCE;

D O I：

10.1027/1614-2241/a000051

中图分类号：

O1 [数学]; C [社会科学总论];

学科分类号：

03 ; 0303 ; 0701 ; 070101 ;

摘要：

Most of the strategies that have been proposed to determine the number of components that account for the most variation in a principal components analysis of a correlation matrix rely on the analysis of the eigenvalues and on numerical solutions. The Cattell's scree test is a graphical strategy with a nonnumerical solution to determine the number of components to retain. Like Kaiser's rule, this test is one of the most frequently used strategies for determining the number of components to retain. However, the graphical nature of the scree test does not definitively establish the number of components to retain. To circumvent this issue, some numerical solutions are proposed, one in the spirit of Cattell's work and dealing with the scree part of the eigenvalues plot, and one focusing on the elbow part of this plot. A simulation study compares the efficiency of these solutions to those of other previously proposed methods. Extensions to factor analysis are possible and may be particularly useful with many low-dimensional components.

引用

页码：23 / 29

页数：7

共 31 条

[1] AN ASYMPTOTIC-EXPANSION FOR THE DISTRIBUTION OF THE LATENT ROOTS OF THE ESTIMATED COVARIANCE-MATRIX [J].